Michael HahslerAssistant Professor
Department of Engineering Management, Information and Systems
M.S. Wirtschaftsuniversität Wien, Austria; Ph.D., Wirtschaftsuniversität Wien, Austria
Data Mining, Machine Learning, Business Analytics, Data Stream Mining, Recommender Systems, Data Visualization, Association Rule Mining, Market Basket Analysis.
Research Accomplishments and Activities
Research sponsored by National Science Foundation, National Institutes of Health and the Austrian Federal Ministry of Research and Education; Lead developer of many R extension packages for data mining and combinatorial optimization; Author of over 50 publications in international journals and conferences.
Michael Hahsler, Sudheer Chelluboina, Kurt Hornik, and Christian Buchta. The arules R-package ecosystem: Analyzing interesting patterns from large transaction datasets. Journal of Machine Learning Research, 12:1977-1981, 2011.
Michael Hahsler and Kurt Hornik. Dissimilarity plots: A visual exploration tool for partitional clustering. Journal of Computational and Graphical Statistics, 10(2):335-354, June 2011.
Michael Hahsler and Margaret H. Dunham. Temporal structure learning for clustering massive data streams in real-time. In SIAM Conference on Data Mining (SDM11), pages 664-675. SIAM, April 2011.
Margaret H. Dunham, Michael Hahsler, and Myra Spiliopoulou. Novel data stream pattern mining, Report on the StreamKDD'10 Workshop. SIGKDD Explorations, 12(2):54-55, 2010.
Rao M. Kotamarti, Michael Hahsler, Douglas Raiford, Monnie McGee, and Margaret H. Dunham. Analyzing taxonomic classification using extensible Markov models. Bioinformatics, 26(18):2235-2241, 2010.
Michael Hahsler and Margaret H. Dunham. rEMM: Extensible Markov model for data stream clustering in R. Journal of Statistical Software, 35(5):1-31, 2010.
Michael Hahsler, Christian Buchta, and Kurt Hornik. Selective association rule generation. Computational Statistics, 23(2):303-315, April 2008.
Michael Hahsler, Kurt Hornik, and Christian Buchta. Getting things in order: An introduction to the R package seriation. Journal of Statistical Software, 25(3):1-34, March 2008.
Michael Hahsler and Kurt Hornik. TSP - Infrastructure for the traveling salesperson problem. Journal of Statistical Software, 23(2):1-21, December 2007.
Michael Hahsler and Kurt Hornik. New probabilistic interest measures for association rules. Intelligent Data Analysis, 11(5):437-455, 2007.
Michael Hahsler. A model-based frequency constraint for mining associations from transaction data. Data Mining and Knowledge Discovery, 13(2):137-166, September 2006.
Christoph Breidert, Michael Hahsler, and Thomas Reutterer. A review of methods for measuring willingness-to-pay. Innovative Marketing, 2(4):8-32, 2006.
Michael Hahsler, Bettina Grün, and Kurt Hornik. arules - A computational environment for mining association rules and frequent item sets. Journal of Statistical Software, 14(15):1-25, October 2005.
Michael Hahsler. Integrating digital document acquisition into a university library: A case study of social and organizational challenges. Journal of Digital Information Management, 1(4):162-171, December 2003.
Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn. Educational and scientific recommender systems: Designing the information channels of the virtual university. International Journal of Engineering Education, 17(2):153-163, 2001.